# Preprint reports shorter agent prompts without loss of task correctness

_Published Monday, October 26, 2026 at 3:35 PM EDT · AI, Science · Latest · Tier 2 — Notable_

Researchers report reducing a production merchant-facing agent's full prompt surface by 3.5-7.6% without reducing correctness on held-out tasks, according to a preprint. The result held across three independent model families, with correctness improving for one.

The method uses an offline evaluation system designed to keep tests reproducible as live enterprise data changes and to regenerate them when stale. It guides prompt optimization through a correctness gate intended to prevent improvements in evaluation scores from masking failures on the actual tasks.

## Sources

- [cs.AI updates on arXiv.org](https://arxiv.org/abs/2610.31972)

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Canonical: https://techandbusiness.org/newswire/Wd4UOjMqjFawO8-ivHZic4
Published: 2026-10-26T19:35:51.338Z
Story chronology: 2026-10-26T04:00:00.000Z
Retrieved: 2026-10-26T23:00:12.859Z
Publisher: Tech & Business (techandbusiness.org)